On June 14th, at the ARF’s Women in Analytics event, thought leaders in the research industry shared best practices and inspiration to help attendees gain ground on their thought leadership path.
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This live panel featured the presenters from the New Methods to Validate Audience Estimates track, with moderator Megan Margraff of Oracle following up on key points involving alternate data currencies, data harmonization and normalization, fragmentation challenges and advanced targeting in TV and CPG.
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Integrating linear TV in cross-platform measurement was a challenge undertaken in a partnership between Lucid and Samba TV utilizing ACR (automatic content recognition) and STB (set-top box) data matched to survey responses. Stephanie Gall (Lucid) and Karen Biedermann (Samba) shared details on the inherent problems, potential solutions and biggest learnings from this integration.
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Programming researchers are not getting the data they need to make informed decisions and Joan FitzGerald (Data ImpacX) uses streaming’s complex ecosystem to explain the conundrum facing programmers. Key insights into monetization and performance are not supported despite the inundation of new forms of data, leaving programmers without a comprehensive picture of their audience. Together with Michael McGuire at MSA, Joan outlined a methodology funnel that combined 1st, 2nd and 3rd party data to create equivalized metrics that, once leveraged, could meet critical programming research demands.
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Pete Doe (Xandr) and Caroline Horner (605) provided a case study of their partnership that derived results from alternative currency measurement with buy and sell side perspectives. Xandr’s nimble workflow method enabled 605’s shift from advanced targeting to a very specific, custom-built, “persuadable” target audience with a range between 2 to 10x increase in outcomes.
Member Only AccessA new study shows that using neuroscience-based methods is likely to increase the accuracy of real-world product sales. Read more »
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It’s no surprise that new product launches often fail to meet their targets. The trick for managers is to improve their predictions for such products. They must balance the costs and benefits of many different data sources and analytic techniques in order to improve forecasting. To enhance the accuracy of predicting the market-level sales of new products, researchers Marton Varga, Anita Tusche, Paulo Albuquerque, Nadine Gier, Bernd Weber, and Hilke Plassmann, analyzed the added value of different data types. Their conclusions are illuminating.
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